A Novel approach of Data Hiding Using Pixel Mapping Method (PMM)

Steganography is a process that involves hiding a message in an appropriate carrier like image or audio. The carrier can be sent to a receiver without any one except the authenticated receiver only knows existence of the information. Considerable amount of work has been carried out by different researchers on steganography. In this work the authors propose a novel Steganographic method for hiding information within the spatial domain of the gray scale image. The proposed approach works by selecting the embedding pixels using some mathematical function and then finds the 8 neighborhood of the each selected pixel and map each two bit of the secret message in each of the neighbor pixel according to the features of that pixel in a specified manner. This approach can be modified for mapping of four bits of the secret message by considering more no of features of the embedding pixel. Before embedding a checking has been done to find out whether the selected pixel or its neighbor lies at the boundary of the image or not. This solution is independent of the nature of the data to be hidden and produces a stego image with minimum degradation.

Steganography is a process that involves hiding a message in an appropriate carrier like image or audio. The carrier can be sent to a receiver without any one except the authenticated receiver only knows existence of the information. Considerable amount of work has been carried out by different researchers on steganography. In this work the authors propose a novel Steganographic method for hiding information within the spatial domain of the gray scale image. The proposed approach works by selecting the embedding pixels using some mathematical function and then finds the 8 neighborhood of the each selected pixel and map each two bit of the secret message in each of the neighbor pixel according to the features of that pixel in a specified manner. This approach can be modified for mapping of four bits of the secret message by considering more no of features of the embedding pixel. Before embedding a checking has been done to find out whether the selected pixel or its neighbor lies at the boundary of the image or not. This solution is independent of the nature of the data to be hidden and produces a stego image with minimum degradation.

—Steganography is a process that involves hiding a mes-sage in an appropriate carrier like image or audio. The carrier can besent to a receiver without any one except the authenticated receiveronly knows existence of the information. Considerable amount of work has been carried out by different researchers on steganography.In this work the authors propose a novel Steganographic method forhiding information within the spatial domain of the gray scale image.The proposed approach works by selecting the embedding pixelsusing some mathematical function and then ﬁnds the 8 neighborhoodof the each selected pixel and map each two bit of the secret messagein each of the neighbor pixel according to the features of that pixelin a speciﬁed manner.This approach can be modiﬁed for mapping of four bits of the secret message by considering more no of features of the embedding pixel. Before embedding a checking has been done toﬁnd out whether the selected pixel or its neighbor lies at the boundaryof the image or not. This solution is independent of the nature of the data to be hidden and produces a stego image with minimumdegradation.

Keywords

—Cover Image, Pixel Mapping Method (PMM), StegoImage.

I. I

NTRODUCTION

S

TEGANOGRAPHY is the art and science of hiding infor-mation by embedding messages within other, seeminglyharmless messages. Steganography means “covered writing” inGreek. As the goal of steganography is to hide the presenceof a message and to create a covert channel, it can be seenas the complement of cryptography, whose goal is to hide thecontent of a message. Another form of information hiding isdigital watermarking, which is the process that embeds datacalled a watermark, tag or label into a multimedia object suchthat watermark can be detected or extracted later to make anassertion about the object. The object may be an image, audio,video or text only. A famous illustration of steganographyis

Simmons’ Prisoners’ Problem

[16].An assumption canbe made based on this model is that if both the senderand receiver share some common secret information thenthe corresponding steganography protocol is known as thenthe secret key steganography where as pure steganographymeans that there is none prior information shared by senderand receiver. If the public key of the receiver is knownto the sender, the steganographic protocol is called publickey steganography [2], [3] and [10].For a more thorough

S. Bhattacharyya is with the Department of Computer Science and Engi-neering, University Institute of Technology, The University of Burdwan, WestBengal, India e-mail: (souvik.bha@gmail.com).L. Kumar is with the Central Institute of Mining and Fuel Research ,Dhanbad, Jharkhand, India e-mail:(lalan.cimfr@gmail.com).G. Sanyal is with with the Department of Computer Science and En-gineering, National Institute of Technologyy West Bengal, India e-mail:(nitgsanyal@gmail.com).

knowledge of steganography methodology the reader maysee [14], [17].Some Steganographic model with high securityfeatures has been presented in [4], [5] and [6].Almost alldigital ﬁle formats can be used for steganography, but theimage and audio ﬁles are more suitable because of their highdegree of redundancy [17]. Fig. 1 below shows the differentcategories of steganography techniques.

Fig. 1. Types of Steganography

A block diagram of a generic image steganographic systemis given in Fig. 2.

Fig. 2. Generic form of Image Steganography

A message is embedded in a digital image (cover image)through an embedding algorithm, with the help of a secret key.The resulting stego image is transmitted over a channel to thereceiver where it is processed by the extraction algorithm usingthe same key. During transmission the stego image, it can bemonitored by unauthenticated viewers who will only noticethe transmission of an image without discovering the existenceof the hidden message. In this work a speciﬁc image basedsteganographic method for gray level image has proposed. Inthis method instead of embedding the secret message into thecover image a mapping technique has been incorporated togenerate the stego image. This method is capable of extractingthe secret message without the presence of the cover image.This paper has been organized as following sections: Sec-tion II describes some related works, Section III deals withproposed method. Algorithms are discussed in Section IVand Experimental results are shown in Section V. Section VI

contains the analysis of the results and Section VII draws theconclusion.II. R

ELATED

W

ORKS

A. Data Hiding by LSB

Various techniques about data hiding have been proposedin literatures. One of the common techniques is based onmanipulating the least-signiﬁcant-bit (LSB) [8], [9] and [13],[15]planes by directly replacing the LSBs of the cover-imagewith the message bits. LSB methods typically achieve highcapacity but unfortunately LSB insertion is vulnerable to slightimage manipulation such as cropping and compression.

B. Data Hiding by PVD

The pixel-value differencing (PVD) method proposed byWu and Tsai [18] can successfully provide both high embed-ding capacity and outstanding imperceptibility for the stego-image. The pixel-value differencing (PVD) method segmentsthe cover image into non overlapping blocks containing twoconnecting pixels and modiﬁes the pixel difference in eachblock (pair) for data embedding. A larger difference in theoriginal pixel values allows a greater modiﬁcation. In theextraction phase, the original range table is necessary. It isused to partition the stego-image by the same method as usedto the cover image. Based on PVD method, various approacheshave also been proposed. Among them Chang et al. [12].proposes a new method using tri-way pixel-value differencingwhich is better than original PVD method with respect to theembedding capacity and PSNR.

C. Data Hiding by GLM

In 2004, Potdar et al.[11] proposes GLM (Gray level mod-iﬁcation) technique which is used to map data by modifyingthe gray level of the image pixels. Gray level modiﬁcationSteganography is a technique to map data (not embed or hideit) by modifying the gray level values of the image pixels.GLM technique uses the concept of odd and even numbersto map data within an image. It is a one-to-one mappingbetween the binary data and the selected pixels in an image.From a given image a set of pixels are selected based on amathematical function. The gray level values of those pixelsare examined and compared with the bit stream that is to bemapped in the image.

In this work [1] a novel Steganographic method for hidinginformation within the spatial domain of the grayscale imagehas been proposed. The proposed approach works by dividingthe cover into blocks of equal sizes and then embeds themessage in the edge of the block depending on the number of ones in left four bits of the pixel.III. P

ROPOSED

M

ETHOD

In this section the authors propose a new method forinformation hiding within the spatial domain of any gray scaleimage.This method can be considered as the improved versionof [7].The input messages can be in any digital form, and areoften treated as a bit stream. Embedding pixels are selectedbased on some mathematical function which depends on thepixel intensity value of the seed pixel and its 8 neighborsare selected in counter clockwise direction. Before embeddinga checking has been done to ﬁnd out whether the selectedembedding pixels or its neighbors lies at the boundary of theimage or not. Data embedding are done by mapping each twoor four bits of the secret message in each of the neighbor pixelbased on some features of that pixel. Fig.5 and Fig.6 showsthe mapping information for embedding two bits or four bitsrespectively.

Fig. 5. Mapping Technique for embedding of two bitsFig. 6. Mapping Technique for embedding of four bits

Extraction process starts again by selecting the same pixelsrequired during embedding. At the receiver side other differentreverse operations has been carried out to get back the originalinformation.

can beselected with row (r) and column (c). Next step is to ﬁndthe 8 neighbors

P

r



c



of the pixel

P

rc

such that

r



=

r

+

l

,

c



=

c

+

l

,

−

1

≤

l

≤

1

. The embedding process will beﬁnished when all the bits of every bytes of secret message aremapped or embedded.

A. Data Embedding Method for embedding of two bits

Algorithm of the embedding method are described as :

•

Input : Cover Image(C), Message (MSG).

•

Find the ﬁrst seed pixel

P

rc

.

•

count

= 1

.

•

while (

count

≤

n

)

•

begin (for embedding message in message surrounding aseed pixel).

•

cnt=Count number of ones of one of the

P

r



c



of intensity(V).

•

m

k

=Get next msg bit.

•

count

=

count

+ 1

.

•

m

k

+1

=Get next msg bit.

•

count

=

count

+ 1

.

•

Bincvr= Binary of V.

•

If(

m

k

= 0 &

m

k

+1

= 1

)

•

Bincvr

(

zerothbit

) = 0

•

If(

cnt

mod 2 = 0

)

•

Bincvr

(

firstbit

) =

¬

Bincvr

(

firstbit

)

•

If(

m

k

= 0 &

m

k

+1

= 0

)

•

Bincvr

(

zerothbit

) = 1

•

If(

cnt

÷

2



= 0

)

•

Bincvr

(

firstbit

) =

¬

Bincvr

(

firstbit

)

•

If(

m

k

= 0 &

m

k

+1

= 0

)

•

Bincvr

(

zerothbit

) = 0

•

If(

cnt

mod 2



= 0

)

•

Bincvr

(

firstbit

) =

¬

Bincvr

(

firstbit

)

•

If(

m

k

= 0 &

m

k

+1

= 1

)

•

Bincvr

(

zerothbit

) = 1

•

If(

cnt

mod 2 = 0

)

•

Bincvr

(

firstbit

) =

¬

Bincvr

(

firstbit

)

•

End

•

Get the next neighbor pixel

P

r



c



for embedding basedon previous

P

r



c



and repeat.

•

End

•

Return the stego image (S).

B. Data Extraction Method for extraction of two bits

The process of extraction proceeds by selecting those samepixel with their neighbors. The extracting process will beﬁnished when all the bits of every bytes of secret message areextracted. Algorithm of the extraction method are describedas :

•

Input : Stego image (S) , count.

•

count

=

count

÷

2

.

Fig. 7. A snapshot of data embedding process for two bitsFig. 8. DFA for embedding process of two bits.

•

BinMsg= ” ”.

•

Find the ﬁrst seed pixel

P

rc

.

•

I=0.

•

While (

count

≤

N

)

•

begin (for extract message in message around a seedpixel).

•

Get the (First/Next) neighbor pixel

P

r



c



.

•

cnt=Count number of ones of one of the

P

r



c



of intensity(V).

•

Bincvr= Binary of V.

•

Binmsg(i)=ZerothBit of Bincvr.

•

count

=

count

+ 1

.

•

i

=

i

+ 1

.

•

Binmsg(i)=Enters according to One of ones in the inten-sity(1 for odd :0 for even).